class_docstr: Default neural network module used in `Neural` mixer to learn the predictive task based on encoded feature representations.
  
  Small architecture with either a one or two linear layers. Hidden size might be constrained to have at most `max_params` in the network, trading off accuracy for speed.
code: def to(self, device: torch.device) -> torch.nn.Module:
      if "cuda" not in str(torch.device) == 0:
          log.warning(
              "Creating neural network on CPU, it will be significantly slower than using a GPU, consider using a GPU instead"
          )  # noqa
      self.net = self.net.to(device)
  
      self.device = device
      return self
  
file_path: lightwood/lightwood/mixer/helpers/default_net.py
imports: import math
  import torch
  from lightwood.helpers.torch import LightwoodAutocast
  from lightwood.helpers.device import get_device_from_name
  from lightwood.helpers.log import log
  import numpy
label_desc: Use image node_id 2 for calling the DefaultNet obj's underlying member method code with example usage: obj.to(device) and returns: self